Course Description
Provides instruction and insights, on a foundational basis, into Data Science, including mathematics, programming, data management, and computer systems. It also develops the skills to apply theory, skills, and toolkits to real-world applications in different industries. The course provides extensive hands-on experience.
Athena Title
Informatics I
Equivalent Courses
Not open to students with credit in INFO 2000E
Semester Course Offered
Offered every year.
Grading System
A - F (Traditional)
Course Objectives
Upon successful completion of this course, students will be able to: • Operate local and remote computer systems using command-line interfaces. • Implement basic mathematical algorithms relevant to data science. • Load data and store results in unstructured and structured forms. • Clean, transform, and combine source data for subsequent analysis. • Summarize and visualize data to produce organized narratives for stakeholders. • Use version control systems and services to manage and collaborate on programming projects.
Topical Outline
Foundational Programming and Mathematics: Linear Algebra Statistics and Probability Data Types Data Structures Control Flow Functions Classes Tools: Python, Numpy Exploratory Data Analysis: Structured Data Unstructured Data Data Organization and Management Data Pre-Processing and Transformation Data Summarization and Visualization Query Language Tools: System I/O, SQLite, Pandas, Matplotlib Software Foundations: Command-line Interfaces Development Environments Version Control Systems Networking Basics for Web Programming Tools: Shell, Cloud services, Flask, Git/Github Clinical Work: Programming Projects - Optimization Programming Projects - Data Pre-Processing Programming Projects - Data Visualization Programming Projects - General Applications
Syllabus